Enterprise Account Executive

Orama Solutions
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Analyst

2x Senior Data Engineer (Financial Services)

Senior Data Engineer

Data Analyst - Sc cleared

Azure Data Engineer

Senior Data Analyst

Orama Solutions are proud to be partnered with an Open Source Data platform flying high after a $30m+ total funding. The product leverages AI and Machine Learning to revolutionise how we utilize data.


The Role

The role is a fully remote Enterprise Account Executive position with a New Business focus selling a Data platform across EMEA.


Company Highlights

  • 300% ARR growth for consecutive years closing last year on $10m ARR.
  • £30m Series A, gearing up for a Series B round.
  • 100 inbound leads per month coming into the sales org.
  • Every ramped rep meeting quota in year one. Top performer at 200%.
  • Hired Reps from leading reps from Astronomer, Databricks, Imply and Dremio.
  • CRO, CMO, BDR team, Presales and Customer Success in place.
  • Closed logo in the Fortune 10 list.
  • 50+ Enterprise customers (Figma, LinkedIn, Notion, PayPal, Riskified, Expedia, etc)
  • Co-Founders former foundational engineers for both Airbnb and LinkedIn.


Product

Metadata platform that drastically reduces cost of data catalogue maintenance by ONLY operating once triggered. This technology is a one stop shop as this data catalog provides solutions for data discovery, governance, lineage and observability!


Experience needed to apply

  • Multiple years of experience in selling Data products and platforms at the Enterprise level in the EMEA territory
  • A strong sales process and a startup mentality. Ideally Series A or B selling experience.
  • Closed Multiple six figure deals.
  • Rolodex of Data personas.
  • Successful track record of over achieving quota with past companies (100%+) for consecutive Financial Years.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.